2009 16th IEEE International Conference on Image Processing (ICIP) 2009
DOI: 10.1109/icip.2009.5413710
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A shape descriptors comparison for organs deformation sequence characterization in MRI sequences

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Cited by 7 publications
(8 citation statements)
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“…Several sd have been experimented, such as the shape signature, the Zernike moments, or the Fourier descriptors. We have shown in [7] that the results of different descriptors are equivalent. We used Fourier descriptors (fd) in this study.…”
Section: Deformation Criteriamentioning
confidence: 82%
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“…Several sd have been experimented, such as the shape signature, the Zernike moments, or the Fourier descriptors. We have shown in [7] that the results of different descriptors are equivalent. We used Fourier descriptors (fd) in this study.…”
Section: Deformation Criteriamentioning
confidence: 82%
“…sd are numerical attributes representing the shape aspect, they are widely used in pattern recognition, a review is proposed in [6]. An adaptation of sd was proposed in [7]: the organ deformation at a given time is represented by the distance between the organ sd coefficients at that time, and the organ sd coefficients at the rest-state (t = 0). Several sd have been experimented, such as the shape signature, the Zernike moments, or the Fourier descriptors.…”
Section: Deformation Criteriamentioning
confidence: 99%
“…Feature extraction 1) Extraction of deformation features: Shape descriptors are widely used in pattern recognition and indexing, a review is proposed in [3]. We detailed the shape descriptors used in [2]. Among the space domain-based descriptors, we have chosen the shape signature, it sums up the radius variations between the shape barycenter and the boundary points.…”
Section: A Datamentioning
confidence: 99%
“…We have developed a methodology which approximates these references from organ contours (see [2]). The anorectal angle is the junction of the rectum with the anus, we have computed this angle by exploiting the curvature properties of the rectum medial axis.…”
Section: ) Extraction Of Displacement Featuresmentioning
confidence: 99%
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